摘要
为了提高商品推荐系统的性能,从理解B2C电子商务平台客户的购物倾向角度出发,进行实时的商品推荐。本文总结归纳了B2C电子商务平台的主要商品推荐位,以及如何基于商品信息建立商品标签,如何判别商品的相似性、相同性。在上述工作的基础上,重点论述了基于客户购物倾向的实时的商品推荐方案。本文对已有工作进行了深入对比和分析,对提出的方案进行了必要的理论分析和性能评估。并从XBRL的技术角度,对商品推荐方案进行了改进。
To improve the performance of the commodity recommendation system, this paper proposes two methods:(1) recommend commodity in real-time;(2) understand customers’ purchase intentions. In order to achieve the above goals, we summarize commodity recommendation location, and the label of commodity. Based on the above, we propose a scheme to improve the performance of the commodity recommendation system. We conduct an in-depth analysis on existing work, and give necessary theoretical analysis and performance evaluation for the proposed commodity recommend scheme. From the technical point of view, this method improves the above commodity recommend scheme.
出处
《集成技术》
2013年第3期15-21,共7页
Journal of Integration Technology
关键词
购物倾向
商品推荐方案
理论分析
性能评估
XBRL
purchase intention
commodity recommend scheme
theoretical analysis
performance evaluation
XBRL
